scholarly journals Estimating relatedness between malaria parasites

2019 ◽  
Author(s):  
Aimee R. Taylor ◽  
Pierre E. Jacob ◽  
Daniel E. Neafsey ◽  
Caroline O. Buckee
Keyword(s):  
Genetic Epidemiology ◽  
Ad Hoc ◽  
Pathogen Transmission ◽  
Identity By Descent ◽  
Malaria Parasites ◽  
Data Set ◽  
Epidemiology Studies ◽  
Diverse Data ◽  
Prospective Study Design ◽  
Identity By State

1.AbstractUnderstanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites,Plasmodium falciparumandPlasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-by-state are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

scholarly journals Evaluating Metagenomic Analysis for Pathogen Transmission in Healthcare Settings

2020 ◽  
Vol 41 (S1) ◽  
pp. s224-s224
Author(s):  
Curt Hewitt ◽  
Katharina Weber ◽  
Danielle LeSassier ◽  
Anthony Kappell ◽  
Kathleen Schulte ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Dna Analysis ◽  
Pathogen Transmission ◽  
Species Level ◽  
Metagenomic Analysis ◽  
Skin Microbiome ◽  
Limited Information ◽  
Culture Methods ◽  
Data Set ◽  
Skin Contact

Background: The prevalence of healthcare-acquired infections (HAIs) and rising levels of antimicrobial resistance place a significant burden on modern healthcare systems. Cultures are typically used to track HAIs; however, culture methods provide limited information and are not applicable to all pathogens. Next-generation sequencing (NGS) can detect and characterize pathogens present within a sample, but few research studies have explored how NGS could be used to detect pathogen transmission events under HAI-relevant scenarios. The objective of this CDC-funded project was to evaluate and correlate sequencing approaches for pathogen transmission with standard culture-based analysis. Methods: We modeled pathogen transfer via hand contact using synthetic skin. These skin coupons were seeded with a community of commensal organisms to mimic the human skin microbiome. Pathogens were added at physiologically relevant high or low levels prior to skin-to-skin contact. The ESKAPE pathogens: E. faecium, S. aureus, K. pneumoniae, A. baumannii, P. aeruginosa, and Enterobacter spp plus C. difficile were employed because they are the most common antibiotic resistant HAIs. Pathogen transfer between skin coupons was measured following direct skin contact and fomite surface transmission. The effects of handwashing or fomite decontamination were also evaluated. Transferred pathogens were enumerated via culture to establish a robust data set against which DNA and RNA sequence analyses of the same samples could be compared. These data also provide a quantitative assessment of individual ESKAPE+C pathogen transfer rates in skin contact scenarios. Results: Metagenomic and metatranscriptomic analysis using custom analysis pipelines and reference databases successfully identified the commensal and pathogenic organisms present in each sample at the species level. This analysis also identified antibiotic resistance genes and plasmids. Metatranscriptomic analysis permitted not only gene identification but also confirmation of gene expression, a critical factor in the evaluation of antibiotic resistance. DNA analysis does not require cell viability, a key differentiator between sequencing and culturing reflected in simulated handwashing data. Sensitivity remains a key limitation of metagenomic analysis, as shown by the poor species identification and gene content characterization of pathogens present at low abundance within the simulated microbial community. Species level identification typically failed as ratios fell below 1:1,000 pathogen CFU:total community CFU. Conclusions: These findings demonstrate the strengths and weaknesses of NGS for molecular epidemiology. The data sets produced for this study are publicly available so they can be employed for future metagenomic benchmarking studies.Funding: NoneDisclosures: None

scholarly journals A likelihood ratio approach for identifying three-quarter siblings in genetic databases

Heredity ◽  
2021 ◽  
Author(s):  
Iván Galván-Femenía ◽  
Carles Barceló-Vidal ◽  
Lauro Sumoy ◽  
Victor Moreno ◽  
Rafael de Cid ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Family Relationships ◽  
Genetic Research ◽  
Data Set ◽  
Scientific Disciplines ◽  
Genome Wide ◽  
Standard Quality ◽  
Control Procedures ◽  
Identity By State ◽  
Second Degree

AbstractThe detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent–offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent–grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method.

Towards a framework for measuring creative economy: evidence from Balkan countries

2019 ◽  
Vol 23 (1) ◽  
pp. 41-62 ◽  
Author(s):  
Valentina Ndou ◽  
Giovanni Schiuma ◽  
Giuseppina Passiante
Keyword(s):  
Business Environment ◽  
Creative Economy ◽  
Data Set ◽  
Content Type ◽  
Balkan Countries ◽  
World Economic ◽  
And Performance ◽  
Diverse Data ◽  
The Relationship ◽  
Performance Dimension

PurposeThe creative process through which the territorial resources, knowledge and culture are used, exploited and configured to match needs and to achieve congruence with the changing business environment has become a crucial process for competitiveness. This is even more relevant for economies of developing countries which are continuously struggling to reap the benefits of globalisation, as well as to grasp the new opportunities for competitiveness. As such, this paper aims to try to concentrate on the dynamic perspectives of the creative economy of countries by distinguishing between the potentialities and performance. The paper tackles the influence that creativity capacities might have on performance of countries.Design/methodology/approachThe methodology consists in identifying creative economy indicators from a diverse data set of the World Economic Forum and distinguish them between potential and performance indicators.FindingsData reveal as good progress and emphasis is being devoted to increasing the level of creativity; however, the Balkan countries still holdup in their capacity to boost innovation.Practical implicationsThe paper provide a new focus of research on creativity measurement that is significant for understanding what creative capacities territories possess and the ability to make proficient use for growth and innovation.Originality/valueThis paper proposes a new operational framework for measuring and interpreting the creative economy indicators by identifying not only indicators that gauge the potentialities of a country, but also indicators that are linked with the performance dimension, as well as the relationship amongst them.

scholarly journals Increased mosquito abundance and species richness in Connecticut, United States 2001–2019

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tanya A. Petruff ◽  
Joseph R. McMillan ◽  
John J. Shepard ◽  
Theodore G. Andreadis ◽  
Philip M. Armstrong
Keyword(s):  
United States ◽  
Species Richness ◽  
Community Composition ◽  
Pathogen Transmission ◽  
Public Health Importance ◽  
Data Set ◽  
Mosquito Abundance ◽  
Total Species Richness ◽  
Multiple Species ◽  
Total Species

Abstract Historical declines in multiple insect taxa have been documented across the globe in relation to landscape-level changes in land use and climate. However, declines have either not been universally observed in all regions or examined for all species. Because mosquitoes are insects of public health importance, we analyzed a longitudinal mosquito surveillance data set from Connecticut (CT), United States (U.S.) from 2001 to 2019 to identify changes in mosquito community composition over time. We first analyzed annual site-level collections and metrics of mosquito community composition with generalized linear/additive mixed effects models; we also examined annual species-level collections using the same tools. We then examined correlations between statewide collections and weather variables as well as site-level collections and land cover classifications. We found evidence that the average trap night collection of mosquitoes has increased by ~ 60% and statewide species richness has increased by ~ 10% since 2001. Total species richness was highest in the southern portion of CT, likely due to the northward range expansion of multiple species within the Aedes, Anopheles, Culex, and Psorophora genera. How the expansion of mosquito populations in the northeast U.S. will alter mosquito-borne pathogen transmission in the region will require further investigation.

scholarly journals A computationally tractable birth-death model that combines phylogenetic and epidemiological data

2020 ◽  
Author(s):  
Alexander E. Zarebski ◽  
Louis du Plessis ◽  
Kris V. Parag ◽  
Oliver G. Pybus
Keyword(s):  
Transmission Rate ◽  
Epidemiological Data ◽  
Heterogeneous Data ◽  
Pathogen Transmission ◽  
Data Sources ◽  
Primary Data ◽  
Analytic Approximation ◽  
Data Set ◽  
Combining Data ◽  
Birth Death

Inferring the dynamics of pathogen transmission during an outbreak is an important problem in both infectious disease epidemiology and phylodynamics. In mathematical epidemiology, estimates are often informed by time-series of infected cases while in phylodynamics genetic sequences sampled through time are the primary data source. Each data type provides different, and potentially complementary, insights into transmission. However inference methods are typically highly specialised and field-specific. Recent studies have recognised the benefits of combining data sources, which include improved estimates of the transmission rate and number of infected individuals. However, the methods they employ are either computationally prohibitive or require intensive simulation, limiting their real-time utility. We present a novel birth-death phylogenetic model, called TimTam which can be informed by both phylogenetic and epidemiological data. Moreover, we derive a tractable analytic approximation of the TimTam likelihood, the computational complexity of which is linear in the size of the data set. Using the TimTam we show how key parameters of transmission dynamics and the number of unreported infections can be estimated accurately using these heterogeneous data sources. The approximate likelihood facilitates inference on large data sets, an important consideration as such data become increasingly common due to improving sequencing capability.

scholarly journals Context-Aware Driver’s Behaviour Monitoring System in Vehicular Ad-Hoc Network

2021 ◽  
Vol 10 (2) ◽  
pp. 701-709
Keyword(s):  
Monitoring System ◽  
Ad Hoc Network ◽  
High Speed ◽  
Ad Hoc ◽  
Detection System ◽  
Vehicular Ad Hoc Network ◽  
Context Aware ◽  
Road Accidents ◽  
Road Transportation ◽  
Data Set

The number of deaths resulting from road accidents and mishaps has increased at an alarming rate over the years. Road transportation is the most popularly used means of transportation in developing countries like Nigeria and most of these road accidents are associated with reckless driving habits. Context-aware systems provide intelligent recommendations allowing digital devices to make correct and timely recommendations when required. Furthermore, in a Vehicular Ad-hoc Network (VANET), communication links between vehicles and roadside units are improved thus enabling vehicle and road safety. Hence, a non-intrusive driver behaviour detection system that incorporates context-aware monitoring features in VANET is proposed in this study. By making use of a one-dimensional highway (1D) road with one-way traffic movement and incorporating GSM technology, irregular actions (high speed, alcohol while driving, and pressure) exhibited by drivers are monitored and alerts are sent to other nearby vehicles and roadside units to avoid accidents. The proposed system adopted a real-time VANET prototype with three entities involved in the context-aware driver’s behaviour monitoring system namely, the driver, vehicle, and environment. The analytical tests with actual data set indicate that, when detected, the model measures the pace of the vehicle, the level of alcohol in the breath, and the driver's heart rate in-breath per minute (BPM). Therefore, it can be used as an appropriate model for the Context-aware driver’s monitoring system in VANET.

The Relationship Between Gratitude and Religious Identification of NCAA Athletes: A Replication Study

2021 ◽  
pp. 1-17
Author(s):  
Nicole T. Gabana ◽  
Jeffrey B. Ruser ◽  
Mariya A. Yukhymenko-Lescroart ◽  
Jenelle N. Gilbert
Keyword(s):  
National Collegiate Athletic Association ◽  
Past Research ◽  
Well Being ◽  
Spiritual Identity ◽  
General State ◽  
Data Set ◽  
Religious Identification ◽  
Dispositional Trait ◽  
And Performance ◽  
Diverse Data

A holistic, multicultural approach to student-athlete mental health, well-being, and performance promotes the consideration of spiritual and religious identities in counseling and consultation. Preliminary research supports the interconnectedness of spirituality, religiosity, and gratitude in athletes; thus, this study sought to replicate Gabana, D’Addario, Luzzeri, and Soendergaard's study (2020) and extend the literature by examining a larger, independently sampled, more diverse data set and multiple types of gratitude. National Collegiate Athletic Association Division I–III student-athletes (N = 596) were surveyed to better understand how religious and spiritual identity related to trait, general-state, and sport-state gratitude. Results supported past research; athletes who self-identified as being both spiritual and religious reported greater dispositional (trait) gratitude than those who self-identified as spiritual/nonreligious or nonspiritual/nonreligious. Between group differences were not found when comparing general-state and sport-state gratitude. Findings strengthen and extend the understanding of spirituality, religion, and gratitude in sport. Limitations, practical implications, and future directions are discussed.

Video Data Mining

2011 ◽  
pp. 1185-1189 ◽  
Author(s):  
Jung Hwan Oh ◽  
Jeong Kyu Lee ◽  
Sae Hwang
Keyword(s):  
Data Mining ◽  
Research Area ◽  
Multimedia Databases ◽  
Video Data ◽  
Multimedia Data ◽  
Data Sets ◽  
Data Set ◽  
Useful Knowledge ◽  
Active Research ◽  
Diverse Data

Data mining, which is defined as the process of extracting previously unknown knowledge and detecting interesting patterns from a massive set of data, has been an active research area. As a result, several commercial products and research prototypes are available nowadays. However, most of these studies have focused on corporate data — typically in an alpha-numeric database, and relatively less work has been pursued for the mining of multimedia data (Zaïane, Han, & Zhu, 2000). Digital multimedia differs from previous forms of combined media in that the bits representing texts, images, audios, and videos can be treated as data by computer programs (Simoff, Djeraba, & Zaïane, 2002). One facet of these diverse data in terms of underlying models and formats is that they are synchronized and integrated hence, can be treated as integrated data records. The collection of such integral data records constitutes a multimedia data set. The challenge of extracting meaningful patterns from such data sets has lead to research and development in the area of multimedia data mining. This is a challenging field due to the non-structured nature of multimedia data. Such ubiquitous data is required in many applications such as financial, medical, advertising and Command, Control, Communications and Intelligence (C3I) (Thuraisingham, Clifton, Maurer, & Ceruti, 2001). Multimedia databases are widespread and multimedia data sets are extremely large. There are tools for managing and searching within such collections, but the need for tools to extract hidden and useful knowledge embedded within multimedia data is becoming critical for many decision-making applications.

scholarly journals ACAT1 Benchmark of RANS-Informed Analytical Methods for Fan Broadband Noise Prediction—Part I—Influence of the RANS Simulation

Acoustics ◽  
2020 ◽  
Vol 2 (3) ◽  
pp. 539-578
Author(s):  
Carolin Kissner ◽  
Sébastien Guérin ◽  
Pascal Seeler ◽  
Mattias Billson ◽  
Paruchuri Chaitanya ◽  
...  
Keyword(s):  
Turbulence Model ◽  
Analytical Methods ◽  
Companion Paper ◽  
Broadband Noise ◽  
Operating Conditions ◽  
Navier Stokes ◽  
Data Set ◽  
The Past ◽  
Flow Turbulence ◽  
Diverse Data

A benchmark of Reynolds-Averaged Navier-Stokes (RANS)-informed analytical methods, which are attractive for predicting fan broadband noise, was conducted within the framework of the European project TurboNoiseBB. This paper discusses the first part of the benchmark, which investigates the influence of the RANS inputs. Its companion paper focuses on the influence of the applied acoustic models on predicted fan broadband noise levels. While similar benchmarking activities were conducted in the past, this benchmark is unique due to its large and diverse data set involving members from more than ten institutions. In this work, the authors analyze RANS solutions performed at approach conditions for the ACAT1 fan. The RANS solutions were obtained using different CFD codes, mesh resolutions, and computational settings. The flow, turbulence, and resulting fan broadband noise predictions are analyzed to pinpoint critical influencing parameters related to the RANS inputs. Experimental data are used for comparison. It is shown that when turbomachinery experts perform RANS simulations using the same geometry and the same operating conditions, the most crucial choices in terms of predicted fan broadband noise are the type of turbulence model and applied turbulence model extensions. Chosen mesh resolutions, CFD solvers, and other computational settings are less critical.

Estimating Intersection Control Delay Using Large Data Sets of Travel Time from a Global Positioning System

2005 ◽  
Vol 1917 (1) ◽  
pp. 18-27
Author(s):  
Brian Hoeschen ◽  
Darcy Bullock ◽  
Mark Schlappi
Keyword(s):  
Travel Time ◽  
Traffic Engineering ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Data Set ◽  
Control Delay ◽  
Diverse Data ◽  
Intersection Control ◽  
Better Than

Historically, stopped delay was used to characterize the operation of intersection movements because it was relatively easy to measure. During the past decade, the traffic engineering community has moved away from using stopped delay and now uses control delay. That measurement is more precise but quite difficult to extract from large data sets if strict definitions are used to derive the data. This paper evaluates two procedures for estimating control delay. The first is based on a historical approximation that control delay is 30% larger than stopped delay. The second is new and based on segment delay. The procedures are applied to a diverse data set collected in Phoenix, Arizona, and compared with control delay calculated by using the formal definition. The new approximation was observed to be better than the historical stopped delay procedure; it provided an accurate prediction of control delay. Because it is an approximation, this methodology would be most appropriately applied to large data sets collected from travel time studies for ranking and prioritizing intersections for further analysis.

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